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Data lakehouse innovations advance the three pillars of observability for more collaborative analytics

Dynatrace

Grail combines the big-data storage of a data warehouse with the analytical flexibility of a data lake. With Grail, we have reinvented analytics for converged observability and security data,” Greifeneder says. Logs on Grail Log data is foundational for any IT analytics. Grail and DQL will give you new superpowers.”

Analytics 195
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Why log monitoring and log analytics matter in a hyperscale world

Dynatrace

Log monitoring, log analysis, and log analytics are more important than ever as organizations adopt more cloud-native technologies, containers, and microservices-based architectures. What is log analytics? Log analytics is the process of evaluating and interpreting log data so teams can quickly detect and resolve issues.

Analytics 218
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What is predictive AI? How this data-driven technique gives foresight to IT teams

Dynatrace

But when these teams work in largely manual ways, they don’t have time for innovation and strategic projects that might deliver greater value. By analyzing patterns and trends, predictive analytics helps identify potential issues or opportunities, enabling proactive actions to prevent problems or capitalize on advantageous situations.

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Perform 2023 Guide: Organizations mine efficiencies with automation, causal AI

Dynatrace

They now use modern observability to monitor expanding cloud environments in order to operate more efficiently, innovate faster and more securely, and to deliver consistently better business results. In what follows, we explore some key cloud observability trends in 2023, such as workflow automation and exploratory analytics.

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Weighing the top seven Kubernetes challenges and how to solve them

Dynatrace

Adopting this powerful tool can provide strategic technological benefits to organizations — specifically DevOps teams. This complexity has surfaced seven top Kubernetes challenges that strain engineering teams and ultimately slow the pace of innovation. AI-powered analytics. What is Kubernetes?

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Dynatrace Perform 2024 Guide: Deriving business value from AI data analysis

Dynatrace

‘Composite’ AI, platform engineering, AI data analysis through custom apps This focus on data reliability and data quality also highlights the need for organizations to bring a “ composite AI ” approach to IT operations, security, and DevOps. Causal AI is critical to feed quality data inputs to the algorithms that underpin generative AI.

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IT automation central to navigating cloud complexity and data explosion

Dynatrace

But IT teams need to embrace IT automation and new data storage models to benefit from modern clouds. Log management and analytics have become a particular challenge. Instead, as IT pros adopt IT automation and AIOps (or AI for IT operations), IT teams can focus on innovative, high-value tasks that drive better business outcomes.

Cloud 185